def Report(self, end_day, is_detail=False):
import stock,agl
#成交记录
df = self.df_ChengJiao.loc[:,['成交价格','成交数量','买卖标志','买0卖1','证券代码']]
df.columns = ['price','num','flag','flag2','code']
df['d'] = df.index.astype(str)
df['d'] = df['d'].map(lambda x: str(dateutil.parser.parse(x) + \
datetime.timedelta(minutes=5)))
if is_detail:
agl.print_df(df)
#计算股票市值, 暂时只能处理一只股票的情况
shizhi = 0
close = 0
if len(self.df_stock)>0:
code = self.df_stock.iloc[0]['证券代码']
close = stock.getHisdatDataFrameFromRedis(code,'',end_day).iloc[-1]['c']
num = self.df_stock.iloc[0]['库存数量']
shizhi += float(close)*int(num)
print(self.df_zhijing.tail(n=1))
print('市值:%f,总资产:%f'%(shizhi, self.money+shizhi))
#如果持股不动，现在的资金
#取第一次交易后的可用资金
if len(self.df_zhijing)>1:
money = self.df_zhijing.iloc[1]['可用']
else:
money = self.df_zhijing.iloc[0]['可用']
#第一次股票数量到现在的市值
num = 0
if len(self.df_ChengJiao)>0:
num = self.df_ChengJiao.iloc[0]['成交数量']
shizhi = num*close
print('如果持股不动 市值:%f,总资产:%f'%(shizhi, money+shizhi))
def getTradeDay(d1, d2, dtype=backtest_runner.BackTestPolicy.enum.hisdat_mode):
"""确定是交易日
return: (d1, d2)"""
if dtype == backtest_runner.BackTestPolicy.enum.hisdat_mode:
df = stock.getHisdatDataFrameFromRedis(code, start_day=d1)
else:
df = stock.getFenshiDfUseRedis(code, d1, d2)
d2 = agl.datetime_to_date(df.index[-1])
if agl.DateTimeCmp(d1, agl.datetime_to_date(df.index[0])) <0:
d1 = agl.datetime_to_date(df.index[0])
return d1, d2
def genOne(code):
#print code
#先清理5分钟分时redis
stock.FenshiCodeCache(code).delKey()
try:
#通过日线来取最近的5天
df_hisdat = stock.getHisdatDataFrameFromRedis(code)
df_hisdat = df_hisdat.tail()
start_day = agl.datetime_to_date(df_hisdat.index[0])
end_day = agl.datetime_to_date(df_hisdat.index[-1])
df_fenshi = stock.getFenshiDfUseRedis(code, start_day,
end_day).dropna()
except:
return
stock.FenshiCodeCache(code).set(df_fenshi)
def getTradeDay(d1, d2, dtype=backtest_runner.BackTestPolicy.enum.hisdat_mode):
"""确定是交易日
return: (d1, d2)"""
try:
if dtype == backtest_runner.BackTestPolicy.enum.hisdat_mode:
df = stock.getHisdatDataFrameFromRedis(code, d1, d2)
else:
df = stock.getFenshiDfUseRedis(code, d1,d2)
if len(df) == 0:
#在指定日期内没有数据，应该是新股或次新股
return d2,d2
d2 = agl.datetime_to_date(df.index[-1])
if agl.DateTimeCmp(d1, agl.datetime_to_date(df.index[0])) <0:
d1 = agl.datetime_to_date(df.index[0])
except:
pass
return d1, d2
def Report(self, end_day, is_detail=False):
if sys.version > '3':
print('python 3 can not execute')
return
import stock, myredis, mysql, agl
#成交记录
df = self.df_ChengJiao.loc[:, ['成交价格', '成交数量', '买卖标志', '证券代码']]
#print df
#输出交易记录到json，供iChat访问
df.columns = ['price', 'num', 'flag', 'code']
df['d'] = df.index.astype(str)
df['d'] = df['d'].map(lambda x: str(dateutil.parser.parse(x) + \
datetime.timedelta(minutes=5)))
myredis.set_obj('backtest_trade', df)
#原有的php需要使用json， 现在使用django， 可以废弃
#f = open('E:/Apache/Apache/htdocs/stock/trade_training/trade.json','w')
#json.dump(np.array(df).tolist(),f)
#f.close()
if is_detail:
agl.print_df(df)
#计算股票市值, 暂时只能处理一只股票的情况
shizhi = 0
close = 0
if len(self.df_stock) > 0:
code = self.df_stock.iloc[0]['证券代码']
close = stock.getHisdatDataFrameFromRedis(code, '',
end_day).iloc[-1]['c']
num = self.df_stock.iloc[0]['库存数量']
shizhi += float(close) * int(num)
print(self.df_zhijing.tail(n=1))
print('市值:%f,总资产:%f' % (shizhi, self.money + shizhi))
#如果持股不动，现在的资金
#取第一次交易后的可用资金
if len(self.df_zhijing) > 1:
money = self.df_zhijing.iloc[1]['可用']
else:
money = self.df_zhijing.iloc[0]['可用']
#第一次股票数量到现在的市值
num = 0
if len(self.df_ChengJiao) > 0:
num = self.df_ChengJiao.iloc[0]['成交数量']
shizhi = num * close
print('如果持股不动 市值:%f,总资产:%f' % (shizhi, money + shizhi))
def _test_AsynDrawKline(self):
code = '300033'
start_day = '2017-3-1'
df = stock.getHisdatDataFrameFromRedis(code, start_day)
df = stock.getFiveHisdatDf(code, start_day='2017-7-20')
import account
account = account.LocalAcount(account.BackTesting())
#随机找三个交易点
indexs = agl.GenRandomArray(len(df), 3)
trade_bSell = [0, 1, 0]
df_trades = df[df.index.map(lambda x: x in df.index[indexs])]
df_trades = df_trades.copy()
df_trades[AsynDrawKline.enum.trade_bSell] = trade_bSell
plt.ion()
for i in range(10):
AsynDrawKline.drawKline(df[i * 10:], df_trades)
plt.ioff()
plt.show() #最后停在画面处， 没有的话进程结束
def test_drawKlin(self):
code = jx.THS
df = stock.getHisdatDataFrameFromRedis(code)
drawKline(pl, df, legend2=['成交量'])
def test_drawKline():
code, start_day, end_day = '600100', '', ''
df = stock.getHisdatDataFrameFromRedis(code, '', '')
code = stock.getDapanCode(code)
df_dp = stock.getHisdatDataFrameFromRedis(code, start_day, end_day)
drawKline(pl, df_code=df, df_dp=df_dp)
